AIMC Topic: Algorithms

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Impact of artificial intelligence on pathologists' decisions: an experiment.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The accuracy of artificial intelligence (AI) in medicine and in pathology in particular has made major progress but little is known on how much these algorithms will influence pathologists' decisions in practice. The objective of this pape...

DNAffinity: a machine-learning approach to predict DNA binding affinities of transcription factors.

Nucleic acids research
We present a physics-based machine learning approach to predict in vitro transcription factor binding affinities from structural and mechanical DNA properties directly derived from atomistic molecular dynamics simulations. The method is able to predi...

Physics-informed neural networks based on adaptive weighted loss functions for Hamilton-Jacobi equations.

Mathematical biosciences and engineering : MBE
Physics-informed neural networks (PINN) have lately become a research hotspot in the interdisciplinary field of machine learning and computational mathematics thanks to the flexibility in tackling forward and inverse problems. In this work, we explor...

Prespecified-time bipartite synchronization of coupled reaction-diffusion memristive neural networks with competitive interactions.

Mathematical biosciences and engineering : MBE
In this paper, we investigate the prespecified-time bipartite synchronization (PTBS) of coupled reaction-diffusion memristive neural networks (CRDMNNs) with both competitive and cooperative interactions. Two types of bipartite synchronization are con...

Clinical Validation and Extension of an Automated, Deep Learning-Based Algorithm for Quantitative Sinus CT Analysis.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Sinus CT is critically important for the diagnosis of chronic rhinosinusitis. While CT is sensitive for detecting mucosal disease, automated methods for objective quantification of sinus opacification are lacking. We describe ...

[Rapid identification of geographic origins of Zingiberis Rhizoma by NIRS combined with chemometrics and machine learning algorithms].

Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica
In this study, 280 batches of Zingiberis Rhizoma samples from nine producing areas were analyzed to obtain infrared spectral information based on near-infrared spectroscopy(NIRS). Pluralistic chemometrics such as principal component analysis(PCA), pa...

Research on multi-parameter fusion non-invasive blood glucose detection method based on machine learning.

European review for medical and pharmacological sciences
OBJECTIVE: Traditional blood glucose testing methods have several disadvantages, such as high pain and poor acquisition continuity. In response to these shortcomings, we propose a multi-parameter fusion non-invasive blood glucose detection method tha...

Two-Phase Deep Learning Algorithm for Detection and Differentiation of Ewing Sarcoma and Acute Osteomyelitis in Paediatric Radiographs.

Anticancer research
BACKGROUND/AIM: Ewing sarcoma is a highly malignant tumour predominantly found in children. The radiological signs of this malignancy can be mistaken for acute osteomyelitis. These entities require profoundly different treatments and result in comple...

Clinical validation of deep learning algorithms for radiotherapy targeting of non-small-cell lung cancer: an observational study.

The Lancet. Digital health
BACKGROUND: Artificial intelligence (AI) and deep learning have shown great potential in streamlining clinical tasks. However, most studies remain confined to in silico validation in small internal cohorts, without external validation or data on real...